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Results 1 - 3 of 3 for TfRecordRepresentativeDatasetSaver (0.64 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/python/representative_dataset_test.py
num_samples = 2 def data_gen(): for _ in range(num_samples): yield {'x': [1, 2]} repr_ds_map = {'serving_default': data_gen()} saver = repr_dataset.TfRecordRepresentativeDatasetSaver(path_map) dataset_file_map = saver.save(repr_ds_map) self.assertCountEqual(dataset_file_map.keys(), ['serving_default']) dataset_map = repr_dataset.TfRecordRepresentativeDatasetLoader(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jan 04 07:35:19 UTC 2024 - 11.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/representative_dataset.py
""" raise NotImplementedError('Method "save" is not implemented.') @tf_export.tf_export( 'quantization.experimental.TfRecordRepresentativeDatasetSaver' ) class TfRecordRepresentativeDatasetSaver(RepresentativeDatasetSaver): """Representative dataset saver in TFRecord format. Saves representative datasets for quantization calibration in TFRecord format.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 22 22:55:22 UTC 2024 - 14.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/quantize_model.py
_, path_map[signature_key] = tempfile.mkstemp( suffix='.tfrecord', prefix=signature_key ) expected_input_key_map[signature_key] = signature_def.inputs.keys() return repr_dataset.TfRecordRepresentativeDatasetSaver( path_map=path_map, expected_input_key_map=expected_input_key_map, ).save(representative_dataset_map) def _run_static_range_qat( src_saved_model_path: str,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 03:36:50 UTC 2024 - 34.2K bytes - Viewed (0)